Data consolidation in addresses enables automatic planning

Bastian Späth, CEO/Vorstand EIKONA AG
Employee checks address in software while standing at shipping table in warehouse.

It's an everyday struggle in freight forwarding: suppliers and shippers use dozens of different spellings for one and the same recipient. What often works smoothly in delivery proves to be a major obstacle for all other business processes in logistics. The best remedy is to consolidate the address data, turning many different versions into a standardised one.

It's human nature to describe things differently: colours, shapes, tastes and smells. Everyone perceives things differently, after all. That is why address standardisation systems have been developed to present facts as uniformly as possible. It works well for letters, parcels and the delivery of freight forwarding shipments, too. Data evaluation, however, is trickier. IT systems inherently take a different approach to handling data. They can only determine whether values are identical or different, not whether they are similar. Assignments are based entirely on formal criteria: Royal Mail, Royal Mail Group, Parcelforce or even the Post Office – for an address management system, this would be four different recipients, even if they are located at the same address. So, based on this information, an automated dispatching system would likely plan for four different destinations – and might not load the shipments onto the same vehicle. The only way to change this is for the software to recognise the similarities.

What happens to addresses during data consolidation?

As a rule, freight forwarding software treats addresses as master data and uses them exactly as they were entered with the order. That is why some logistics service providers use address consolidation software that is capable of merging data records. This kind of solution accesses different data sources and checks the addresses for consistency row by row, column by column, and cell by cell – usually starting from the mailing address in standardised notation. It compares a company's name on the address label with the company's official registered name. Through an interface with Deutsche Post's Addressfactory, it can even use Deutsche Post's postal reference database to determine deliverability, in addition to address information, for the names of private individuals. This system uses fuzzy logic to identify the same recipient in different source data and source systems and generates a standardised address from this information. It standardises:

  • Spellings
  • Formatting
  • Abbreviations
  • Additions

How is consolidated data used?

Themain task of address consolidation is to cleanse the master data and thus ensure a standardised database. That is why data consolidation systems are especially used in companies that have multiple locations. For them, the benefits of linking and automatically merging data in the same database are particularly high. This applies to logistics groups, collaboration networks and the various offices of a freight forwarding company. For them, data quality improves significantly when data integration enables them to make the same data records available to all employees in one application. With the consolidated values, they can automate logistics operations such as dispatch and trip planning and analyse delivery rate and quality.

Data consolidation and data integration improve addresses

When logistics service providers opt for address consolidation, they also improve data integration within their company and eliminate data silos. This pays off in both operational and efficiency terms because all the users across the entire company can access the same data that is available to each individual application. When different entries are made, the consolidated address appears automatically – an important step towards better quality.


Avoid errors in addresses through data consolidation

The advantages of consolidating addresses in logistics databases are legion: clarity, fewer errors, automatic planning and, last but not least, faster and more consistent analyses. In addition, an automated process can help standardize data quality as an adjunct to personal attention and diligence. A smart solution for a difficult and important task!

Bastian Späth
Bastian Späth

As a college-educated computer scientist, Bastian Späth understands how IT solutions are developed from the ground up. For more than 15 years, he has spent every workday collecting requirements, finding ideas, developing designs, setting up projects and getting them safely across the finish line.

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